Association of TFPI with antemortem dementia and postmortem micro brain infarcts

描述(申请人提供)：2001年，全球痴呆症患者人数约为2400万人，预计到2040年将增加到8400万人。血管因素似乎是痴呆的主要组成部分，包括那些涉及凝血的因素。组织因子途径抑制物(TFPI)是组织因子的主要生理抑制物，是血管受损后凝血的起始剂，FXA是凝血系统的主要组成部分，产生大量凝血酶导致血栓形成。TFPI存在于内皮细胞、血小板或血浆中。在PLASA中，它要么与血浆脂蛋白结合，主要是低密度脂蛋白，抗凝活性较低 或以活动的自由非绑定形式。另一种抗凝蛋白，S蛋白(PS)，直接与TFP相互作用，促进对FXA的增强抑制。TFPI-/-和PRO-/-小鼠的模型在子宫中死亡，并在大脑中有血管内纤维蛋白凝块。血浆TFPI和PS浓度的正常变化受到各自结构基因多态性的强烈影响。一些TFPI和PS基因的多态性与深静脉血栓形成有关，然而，这两个相互作用的蛋白的多态性是否会导致微型脑梗塞和痴呆尚不清楚。初步数据表明，缺乏内皮细胞或血小板TFPI的小鼠模型优先在脑内产生血管内纤维蛋白微凝块，这表明临界量的TFPI和/或PS对于防止大脑中的异常凝血是必要的。我们的实验室拥有技术，可以使用NHLBI BioLINCC火奴鲁鲁心脏项目的DNA和血浆样本将小鼠模型的数据转换为人类痴呆症的疾病，该项目由居住在火奴鲁鲁的同质日裔和日裔美国人组成。令人感兴趣的是404名患有和不患有痴呆症的人，他们后来进行了尸检，其中以脑病理为特征。在Aim1中，我们将对所有个体的TFPI基因外显子和5‘端启动子区进行测序，以确定是否存在多态性，并将其与TFPI血药浓度和抗FXA活性相关联。在AIM2中，我们将确定具有PS 196K和GT；E多态的个体，这种多态在日本人群中是唯一发现的，并将该多态与PS血浆浓度和抗血栓活性相关联。在AIM3中，我们将TFPI的血浆浓度和活性与先前已确定的队列的脂蛋白水平和ApoE基因相关联。在这些研究的结论中，我们将确定与痴呆相关的TFPI多态，并用这些多态测定TFPI的血浆浓度和活性，确定196K和GT；E PS多态与痴呆的关系，以及PS的相关血浆浓度和活性与痴呆的关系，并确定TFPI与ApoE的关系。最后，在BioLINCC数据库中发现的其他心血管疾病风险因素将被用于线性回归模型，以确定TFPI和PS在痴呆症发病机制中的重要性。

DESCRIPTION (provided by applicant): In 2001, the world wide number of patients with dementia was approximately 24 million and is expected to increase to 84 million people by the year 2040. Vascular factors appear to be a major component to dementia including those factors involving coagulation. Tissue Factor Pathway Inhibitor (TFPI) is the primary physiological inhibitor of tissue factor, the initiator of clotting after a blood vessel has been damaged, and FXa, a major component of the clotting system that produces a large amount of thrombin resulting in clot formation. TFPI is found in endothelial cells, in platelets or in plasma. In plasa it is either bound to the plasma lipoproteins, predominately LDL, with less anti-coagulant activity or in an active free unbound form. Another anti-coagulant protein, Protein S (PS), directly interacts with TFPI promoting an enhanced inhibition of FXa. Mouse models of either tfpi-/- and pros-/- mice die in utero and have intravascular fibrin clots in the brain. Normal variations in plasma TFPI and PS concentrations are strongly influenced by polymorphisms in their respective structural genes. Several TFPI polymorphisms and PS polymorphisms have been associated with deep vein thrombosis, however, it is not known if polymorphisms of these two interactive proteins cause micro- brain infarcts and dementia. Preliminary data demonstrate that mouse models lacking either endothelial cell or platelet TFPI produce intravascular fibrin micro-clots preferentially in the brain suggesting a critical amount of TFPI and /or PS are necessary to prevent abnormal clotting in the brain. We have techniques available within our laboratory to translate the data from mouse models to the disease of human dementia using DNA and plasma specimens from the NHLBI BioLINCC Honolulu Heart Project consisting of a homogenous population of Japanese and Japanese-Americans residing in Honolulu. Of interest are the 404 individuals with and without dementia who later came to autopsy in which brain pathology was characterized. In Aim1 we will sequence the exons and 5' promoter region of the TFPI gene in all individuals to identify any polymorphisms and correlate the polymorphisms with TFPI plasma concentrations and anti-FXa activity. In Aim2 we will identify individuals with the PS 196K>E polymorphism which is found uniquely in the Japanese population and correlate this polymorphism with the PS plasma concentration and anti-thrombotic activity. In Aim3 we will correlate the TFPI plasma concentrations and activity with lipoprotein levels and ApoE genotype of the cohort which have been previously determined. At the conclusion of these studies, we will have identified TFPI polymorphisms associated with dementia and determined the TFPI plasma concentrations and activity with the polymorphisms, determined the relationship of the 196K>E PS polymorphism to dementia and correlated the associated plasma concentration and activity of PS with dementia, and determined the relationship of TFPI to ApoE. Finally, other risk factors of cardiovascular disease found within the BioLINCC database will be used in a linear regression model to determine the significance of TFPI and PS on the pathogenesis of dementia.